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Article Dans Une Revue Parallel Processing Letters Année : 2003

Pipelining a Skew-Insensitive Parallel Join Algorithm

Résumé

Most standard parallel join algorithms try to overcome data skews with a relatively static approach. The way they distribute data (and then computation) over nodes depends on a data re-distribution algorithm (hashing or range partitioning) that is determined before the actual join begins. On the contrary we choose to pre-scan data in order to choose an efficient join method for each given value of the join attribute. This approach has already proved to be efficient both theoretically and practically in our previous papers. In this paper we introduce a new pipelined version of our frequency adaptive join algorithm. The use of pipelining offers flexible strategies for resource allocation while avoiding unnecessary disk input/output of intermediate join result when computing multi-join queries. We present a detailed version of the algorithm and a cost analysis based on the BSP model, showing that our pipelined algorithm achieves noticeable improvements compared to the one-step version. We thus show that the frequency adaptive approach remains efficient for pipelined multi-join queries.
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Dates et versions

hal-00081339 , version 1 (22-06-2006)

Identifiants

  • HAL Id : hal-00081339 , version 1

Citer

Mostafa Bamha, Matthieu Exbrayat. Pipelining a Skew-Insensitive Parallel Join Algorithm. Parallel Processing Letters, 2003, 13, Number 3, p. 317-328. ⟨hal-00081339⟩
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